Modifications to single-step adversarial training based on empirical properties of iterative methods improve accuracy by up to 16.93% against iterative attacks while reducing training cost by 28.75%.
Towards evaluating the robustness of neural networks,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Using Intuition from Empirical Properties to Simplify Adversarial Training Defense
Modifications to single-step adversarial training based on empirical properties of iterative methods improve accuracy by up to 16.93% against iterative attacks while reducing training cost by 28.75%.